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We consider a capacity expansion problem arising in the design of service
networks. In this context we consider a multi commodity service network that may face several possible non-simultaneous failure scenarios. These scenarios may affect available capacities on links as well as the point-to point demands. The problem is to install capacities on links in the network to meet all point-to-point demands under all failure scenarios while minimizing cost. This class of problems is commonly referred to as the \textit{Survivable Network Design Problem}.\\
We formulate this problem as a mixed integer program and describe a two-stage optimization approach for solving it. In two-stage network optimization, one defers a subset of decisions until after the realization of a failure scenario. Our first stage decisions expand link capacities while second stage decisions represent a recourse action on how to route flows through network paths to meet all point-to-point demands under each failure scenario. Availability of such a recourse action in the second stage allows the decision maker to come up with less conservative solutions in the first stage.\\
We investigate structural properties of our model and present methods leading to
the reduction of solution space and providing upper and lower bounds for our cost function. Bender's decomposition of our formulation leads to a pure-integer master problem including binary capacity expansion decisions and linear sub-problems comprising flow decisions.  Computational experiments are done on a set of instances arising from a real life ATM network using SAS/OR 12.1 and numerical results are presented.
\end{abstract}


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%% -------------------------------- Dedication ------------------------------ %%
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%% \centering To my parents.
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